WO2009097763A1 - Procédé et dispositif de quantification d'un gain - Google Patents

Procédé et dispositif de quantification d'un gain Download PDF

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Publication number
WO2009097763A1
WO2009097763A1 PCT/CN2009/070119 CN2009070119W WO2009097763A1 WO 2009097763 A1 WO2009097763 A1 WO 2009097763A1 CN 2009070119 W CN2009070119 W CN 2009070119W WO 2009097763 A1 WO2009097763 A1 WO 2009097763A1
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Prior art keywords
codebook gain
fixed codebook
gain
subframe
quantization
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Application number
PCT/CN2009/070119
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English (en)
Chinese (zh)
Inventor
Tao Zhang
Hai Zhang
Xin Li
Jialin He
Dejun Zhang
Longyin Chen
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Huawei Technologies Co., Ltd.
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Application filed by Huawei Technologies Co., Ltd. filed Critical Huawei Technologies Co., Ltd.
Publication of WO2009097763A1 publication Critical patent/WO2009097763A1/fr

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Classifications

    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
    • G10L19/04—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using predictive techniques
    • G10L19/08—Determination or coding of the excitation function; Determination or coding of the long-term prediction parameters
    • G10L19/083—Determination or coding of the excitation function; Determination or coding of the long-term prediction parameters the excitation function being an excitation gain

Definitions

  • the present invention relates to coding techniques, and in particular, to a gain quantization method and apparatus.
  • CELP Code Excited Linear Prediction
  • This model is derived from its inverse process, that is, F(z) is used to remove the near-point redundancy of the speech signal, and P(z) is used to remove the far-point redundancy of the speech signal, which is obtained through two-stage prediction.
  • the normalized residual signal approximates the standard normal distribution.
  • the excitation signal of this model is usually selected from the codebook composed of Gaussian white noise sequences, so it is called code excitation linear prediction model.
  • the quantization of the adaptive codebook gain (pitch gain) ga and the fixed codebook gain gs has a great influence on the quality of the synthesized speech. If the gain quantization is coarse, the quantization noise of the synthesized speech is synthesized. Larger, the naturalness and sharpness of synthesized speech are poor. High-quality speech coding algorithms require high-quality gain quantization.
  • the principle of gain quantization for adaptive codebook gain and fixed codebook gain is to make original speech and reconstructed speech. The perceptual weighted mean square error is minimized.
  • the gain of one frame signal is quantized with 30 bits:
  • the estimated energy value for fixed codebook gain prediction is quantized by 2 bits per frame, one frame signal is divided into four sub-frames, and the adaptive codebook and fixed code of each sub-frame are used.
  • the energy of each sub-frame is calculated by equation (1):
  • N 64 is the subframe
  • c (i) is the fixed codebook excitation
  • g c is the fixed-codebook gains
  • codebook is the average energy, which may preclude the use of calculation of formula (2):
  • N-1 can obtain the estimated energy value of the fixed codebook according to formula (1) as shown in equation (3):
  • the average residual energy of each frame can be calculated, which can be calculated by the formula (6):
  • ⁇ is the cross-correlated normalized energy average obtained by removing the two open-loop pitch analysis
  • 10R is the contribution estimate of the adaptive codebook
  • the estimated energy value is quantized with 2 bits to obtain a fixed codebook gain, and the quantization level can be 18, 30, 42, 54.
  • the adaptive codebook gain and the correction factor for each subframe are combined with the 7-bit joint vector quantization, specifically two-dimensional vector quantization, to complete the gain quantization of one frame of the signal.
  • the embodiment of the present invention provides a gain quantization method and apparatus.
  • the technical solution provided by the embodiment of the present invention may not quantize the estimated energy value, thereby saving quantization bits.
  • the invention provides a gain quantization method, comprising:
  • the prediction coefficients of the fixed codebook gains of the remaining subframes are quantized.
  • the present invention also provides a computer program product comprising computer program code, wherein when the computer program code is executed by a computer, the computer program code can cause the computer to perform any of the gain quantization methods A step.
  • the present invention also provides a computer readable storage medium, the computer storing computer program code, when the computer program code is executed by a computer, the computer program code can cause the computer to perform any of gain quantization methods A step.
  • the invention also provides a gain quantization device, comprising:
  • a fixed codebook gain calculation unit for calculating a fixed codebook gain of at least one subframe of a frame signal
  • a fixed codebook gain quantization unit configured to quantize the fixed codebook gain calculated by the fixed codebook gain calculation unit to obtain a quantized value of the fixed codebook gain of the at least one subframe
  • a coefficient calculation unit configured to: Calculating a prediction coefficient of a fixed codebook gain of the remaining subframes using a quantized value of the fixed codebook gain and a fixed codebook gain of the remaining subframes of the one frame signal;
  • a coefficient quantization unit configured to: The prediction coefficients of the fixed codebook gains of the remaining sub-frames are quantized.
  • the embodiment of the present invention uses the quantized value of the fixed codebook gain of the first subframe to calculate the prediction coefficient of the fixed codebook gain of the remaining subframes, thereby making the remaining sub
  • the prediction coefficient of the fixed codebook gain of the frame is related to the quantized value of the fixed codebook gain of the first subframe, which fully utilizes the strong correlation of the fixed codebook gain between each subframe, so that the estimated energy value does not need to be calculated. It is also not necessary to quantify the estimated energy value, so that bits that require quantization of the estimated energy value can be saved.
  • Embodiment 1 is a flowchart of Embodiment 1 of a gain quantization method according to an embodiment of the present invention
  • Embodiment 2 is a flowchart of Embodiment 2 of a gain quantization method according to an embodiment of the present invention
  • Embodiment 3 is a structural diagram of Embodiment 1 of a gain quantization apparatus according to an embodiment of the present invention.
  • FIG. 4 is a structural diagram of Embodiment 2 of a gain quantization apparatus according to an embodiment of the present invention.
  • FIG. 1 is a flowchart of a first embodiment of a gain quantization method according to an embodiment of the present invention, including: Step 101: Calculating a fixed codebook gain of a subframe in a frame signal;
  • the above one subframe is any one of the one frame signals, but the embodiment of the present invention preferably uses the first subframe of the one frame signal;
  • the embodiment of the present invention does not limit the calculation of the fixed codebook gain of only one subframe in a frame signal, and may also calculate the fixed codebook gain of more than one subframe. In the following embodiments, the calculation is used.
  • the fixed codebook gain of one subframe is described, but is not intended to limit the embodiments of the present invention.
  • the process of calculating the fixed codebook gain of one or more subframes is substantially the same as the process of calculating the fixed codebook gain of one subframe, which is not described in detail in the embodiments of the present invention.
  • the fixed codebook gain can be calculated by using a conventional fixed codebook gain calculation method, and the fixed codebook gain can be calculated by other methods; how to calculate the fixed codebook gain does not affect the implementation of the embodiment of the present invention. Therefore, the embodiment of the present invention does not limit the specific calculation process of the fixed codebook gain.
  • a method for calculating a fixed codebook gain according to an embodiment of the present invention is performed by using the following formula (9) Calculation:
  • vector z is the convolution of the fixed codebook vector and the pulse of the perceptually weighted synthesis filter
  • vector ⁇ 2 is the target vector of the fixed codebook search.
  • Step 102 Quantify a fixed codebook gain to obtain a quantized value of a fixed codebook gain of the one subframe.
  • the fixed codebook gain When the fixed codebook gain is quantized, scalar quantization or vector quantization can be performed. If scalar quantization is performed, the fixed codebook gain can be directly quantized by the quantized step size of the fixed codebook, or it can be fixed. The codebook gain is mapped to the logarithmic domain and then subjected to non-uniform scalar quantization; the adaptive codebook gain of the first subframe can be further quantized, and when the fixed codebook gain is quantized, scalar quantization can be performed.
  • Vector quantization can be performed; if scalar quantization is performed, uniform scalar quantization can be performed directly on the adaptive codebook gain with a uniform quantization step size, or the adaptive codebook gain can be mapped to a logarithmic domain and then non-homogenous scalars can be performed.
  • Step 103 Calculate a fixed codebook gain of the remaining subframes of the one frame signal.
  • the calculation of the fixed codebook gain of the remaining sub-frames may be calculated by using equation (9), or may be calculated by other methods. How to calculate the fixed codebook gain of the remaining sub-frames does not affect the embodiment of the present invention.
  • the implementation of the present invention does not limit the specific calculation process of the fixed codebook gain of the remaining subframes;
  • Step 104 Calculate a prediction coefficient of a fixed codebook gain of the remaining subframes by using a quantized value of the fixed codebook gain of the one subframe and a fixed codebook gain of the remaining subframes of the one frame signal;
  • the prediction coefficients of the fixed codebook gains of the remaining subframes may be calculated by using the quantized values of the fixed codebook gains of the one subframe and the fixed codebook gains of the remaining subframes respectively;
  • Step 105 Quantify the prediction coefficients of the fixed codebook gains of the remaining subframes.
  • the prediction coefficients of the fixed codebook gains of the remaining subframes may be vector quantized or scalar quantized. However, in the embodiment of the present invention, when scalar quantization is performed on the fixed codebook gain of the first subframe, a fixed code for the remaining subframes is preferred.
  • the prediction coefficient of the book gain is vector-quantized, thereby combining scalar quantization and vector quantization to improve the quantization precision.
  • this embodiment uses the quantized value of the fixed codebook gain of the first subframe to calculate the remaining children.
  • the prediction coefficient of the fixed codebook gain of the frame so that the prediction coefficient of the fixed codebook gain of the remaining subframe is correlated with the quantized value of the fixed codebook gain of the first subframe, and the fixed codebook gain between each subframe is fully utilized.
  • the correlation is strong, so that there is no need to calculate the estimated energy value, nor is it necessary to quantize the estimated energy value, so that the bit that needs to quantize the estimated energy value can be saved; when the number of quantization bits is constant, the The quantized bits of the estimated energy value are allocated to the sub-frames in one frame of the signal, thereby increasing the quantization accuracy.
  • FIG. 2 is a flowchart of a second embodiment of a gain quantization method according to an embodiment of the present invention, including: Step 201: Calculating a fixed codebook gain and an adaptive codebook gain of a subframe in a frame signal; Step 202: The fixed codebook gain of the subframe is quantized to obtain a quantized value of the fixed codebook gain of the one subframe;
  • Step 203 Quantify an adaptive codebook of the foregoing one subframe.
  • Steps 202 and 203 do not have a sequence of time
  • Step 204 Calculate a fixed codebook gain and an adaptive codebook gain of the remaining subframes of the one frame signal.
  • Step 205 Calculate a prediction coefficient of a fixed codebook gain of the remaining subframes by using a quantized value of the fixed codebook gain of the one subframe and a fixed codebook gain of the remaining subframes of the one frame signal.
  • Step 206 Quantify the prediction coefficients of the fixed codebook gain and the adaptive codebook gain of the remaining subframes.
  • the prediction coefficient of the fixed codebook gain and the adaptive codebook gain may be vector-quantified into a two-dimensional vector, or scalar quantization may be performed separately.
  • the present embodiment uses the quantized value of the fixed codebook gain of the first subframe to calculate the prediction coefficient of the fixed codebook gain of the remaining subframes, so that the prediction coefficients of the fixed codebook gain of the remaining subframes are first.
  • the quantized value of the fixed codebook gain of each subframe is correlated, and the feature of strong fixed codebook gain between each subframe is fully utilized, so that it is not necessary to calculate the estimated energy value, and it is not necessary to quantify the estimated energy value, so
  • the bit that needs to quantize the estimated energy value is saved; when the number of quantization bits is constant, the quantization bit that should be given the estimated energy value can be allocated to the subframe in one frame signal, thereby increasing the quantization precision.
  • the gain quantization method provided by the embodiment of the present invention is described by taking a gain quantization of a frame signal having 4 subframes as an example.
  • the adaptive codebook gain and the fixed codebook gain of the first subframe of a frame signal are calculated.
  • the adaptive codebook gain and the fixed codebook gain algorithm can be used to calculate the adaptive codebook gain and
  • the fixed codebook gain can also be used to calculate the adaptive codebook gain and the fixed codebook gain according to the minimum mean square error criterion.
  • the adaptive codebook gain calculated according to the minimum mean square error criterion is the optimal adaptive codebook gain
  • the fixed codebook gain calculated according to the minimum mean square error criterion is the optimal fixed codebook gain, which is an embodiment of the present invention.
  • One way to solve for the best adaptive codebook gain and the best fixed codebook gain is as follows:
  • the adaptive codebook gain is denoted by ga
  • the fixed codebook gain is denoted by g s .
  • ga and gs need to satisfy equation (10):
  • g a (2xc[ ⁇ ]xc[2]-c[3]xc[4])/(c[4]xc[4]-4xc[0]xc[2])
  • the optimal adaptive codebook gain and the best fixed codebook gain are obtained, and the adaptive code is obtained.
  • the book gain and the fixed codebook gain are quantized, and the embodiment of the present invention preferably performs scalar quantization; the scalar quantization may be a scalar quantization or a non-uniform scalar quantization, for example, the scalar quantization may be performed on the gain directly by the quantization step of the uniform hook, Or the gain is first mapped to the logarithmic domain and then scalar quantized; for example, the 5-bit non-uniform scalar quantization is performed on the best fixed codebook gain, first the logarithm of the best fixed codebook gain is multiplied by 10, and its unit is Decibel (dB), and then quantized, the quantization step size can reach 10*lgl0 (3349.654392/15.848932)/31/2, which is 0.375dB, which can guarantee the quantization precision. Since the quantization accuracy can be improved by using the
  • the optimal adaptive codebook is quantized using 4 bits, and the quantization range may be 0.012445-1.296012; 5 The bits are gain quantized for the best fixed codebook gain, and the quantization range can be 15.848932-3349.654392. Since the quantization bit of 9 bits is allocated for the first subframe, the quantization precision of the first subframe can be further improved, and the estimated energy value is not quantized by using 2 bits, thereby improving the utilization of the quantization bits.
  • the prediction coefficient of the codebook gain is quantized by 7 bits.
  • the adaptive codebook gain and the prediction coefficient of the fixed codebook gain are two-dimensionally vector quantized or separately scalar-quantized.
  • vector quantization is preferably performed.
  • the adaptive codebook gain and the prediction coefficient of the fixed codebook gain can be combined into a two-dimensional vector, and the obtained two-dimensional vector is quantized.
  • the above is only a calculation method of the prediction coefficient of the fixed codebook gain provided by the embodiment of the present invention, and the embodiment of the present invention does not limit the prediction coefficient that can only calculate the fixed codebook gain by using the above manner. .
  • the calculation of the fixed codebook gain of the current subframe may be performed by using the method provided by the embodiment of the present invention, or the calculation method of the conventional fixed codebook gain may be used, and the embodiment of the present invention does not limit the fixed code of the current subframe. How to calculate the book gain.
  • the present embodiment uses the quantized value of the fixed codebook gain of the first subframe to calculate the prediction coefficient of the fixed codebook gain of the remaining subframes, so that the prediction coefficients of the fixed codebook gain of the remaining subframes are first.
  • the quantized value of the fixed codebook gain of each subframe is correlated, and the feature of strong fixed codebook gain between each subframe is fully utilized, so that it is not necessary to calculate the estimated energy value, and it is not necessary to quantify the estimated energy value, so Saving bits that need to quantize the estimated energy value; when the number of quantization bits is constant, the quantization bits that should be given the estimated energy value can be allocated to the subframes in one frame signal, thereby increasing the quantization precision; There are no complicated logarithmic and exponential operations, and there is no need to consume a large amount of computation.
  • FIG. 3 is a diagram showing the structure of the first embodiment of the gain quantization apparatus according to the embodiment of the present invention, including:
  • the fixed codebook gain calculating unit 301 is configured to calculate a fixed codebook gain of one subframe in one frame signal; and calculate a fixed codebook gain of the remaining subframes in one frame signal;
  • the fixed codebook gain quantization unit 302 is configured to quantize the fixed codebook gain of one subframe calculated by the fixed codebook gain calculation unit 301 to obtain a quantized value of the fixed codebook gain of the one subframe;
  • the coefficient calculation unit 303 is configured to calculate a prediction coefficient of the fixed codebook gain of the remaining subframes by using the quantized value of the fixed codebook gain of the one subframe and the fixed codebook gain of the remaining subframes;
  • the coefficient quantization unit 304 is configured to quantize the prediction coefficients of the fixed codebook gains of the remaining subframes calculated by the coefficient calculation unit 303.
  • the present embodiment uses the quantized value of the fixed codebook gain of the first subframe to calculate the prediction coefficient of the fixed codebook gain of the remaining subframes, so that the prediction coefficients of the fixed codebook gain of the remaining subframes are first.
  • the quantized value of the fixed codebook gain of the sub-frames is correlated, and the characteristics of the strong codebook correlation between the sub-frames are fully utilized, so that the predicted energy value does not need to be calculated, and the predicted energy value does not need to be quantized.
  • One subframe allocates more quantization bits, increasing the quantization precision of the first subframe.
  • FIG. 4 is a diagram showing a structure of a second embodiment of a gain quantization apparatus according to an embodiment of the present invention, including: a fixed codebook gain calculation unit 401, configured to calculate a fixed codebook gain of one subframe in a frame signal; Fixed codebook gain for the remaining subframes;
  • the adaptive codebook gain calculation unit 402 is configured to calculate an adaptive codebook gain of the one subframe.
  • the fixed codebook gain quantization unit 403 is configured to quantize the fixed codebook gain of the one subframe calculated by the fixed codebook gain calculation unit 401, to obtain a quantized value of the fixed codebook gain of the one subframe;
  • the adaptive codebook gain quantization unit 404 is configured to quantize the adaptive codebook gain of the one subframe obtained by the adaptive codebook gain calculation unit 402.
  • the coefficient calculation unit 405 is configured to calculate a prediction coefficient of the fixed codebook gain of the remaining subframes by using the quantized value of the fixed codebook gain of the one subframe and the fixed codebook gain of the remaining subframes;
  • the coefficient quantization unit 406 is configured to quantize the prediction coefficients of the fixed codebook gains of the remaining subframes calculated by the coefficient calculation unit 405.
  • the present embodiment uses the quantized value of the fixed codebook gain of the first subframe to calculate the prediction coefficient of the fixed codebook gain of the remaining subframes, so that the prediction coefficients of the fixed codebook gain of the remaining subframes are first.
  • the quantized value of the fixed codebook gain of each subframe is correlated, and the feature of strong fixed codebook gain between each subframe is fully utilized, so that it is not necessary to calculate the estimated energy value, and it is not necessary to quantify the estimated energy value, so
  • the bit that needs to quantize the estimated energy value is saved; when the number of quantization bits is constant, the quantization bit that should be given the estimated energy value can be allocated to the subframe in one frame signal, thereby increasing the quantization precision.
  • the prediction coefficients of the fixed codebook gains of the remaining subframes are quantized.
  • the adaptive codebook gain of the one subframe is further quantized.
  • the adaptive codebook gain of the remaining subframes is quantized.
  • the above-mentioned storage medium may be a read only memory, a magnetic disk or an optical disk or the like.

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  • Engineering & Computer Science (AREA)
  • Computational Linguistics (AREA)
  • Signal Processing (AREA)
  • Health & Medical Sciences (AREA)
  • Audiology, Speech & Language Pathology (AREA)
  • Human Computer Interaction (AREA)
  • Physics & Mathematics (AREA)
  • Acoustics & Sound (AREA)
  • Multimedia (AREA)
  • Compression, Expansion, Code Conversion, And Decoders (AREA)

Abstract

L'invention concerne un procédé de quantification de gain comprenant les étapes consistant à calculer le gain du livre de codes fixes d'au moins une sous-trame dans un signal de trame (101) ; quantifier le gain du livre de codes fixes afin d'obtenir la valeur de quantification du gain du livre de codes fixes de la sous-trame ou des sous-trames (102) ; calculer le coefficient prédictif du gain du livre de codes fixes des sous-trames restantes avec la valeur de quantification du gain du livre de codes fixes et le gain du livre de codes fixes des sous-trames restantes du signal de trame (103-104) ; quantifier le coefficient prédictif du gain du livre de codes fixes des sous-trames restantes (105). L'invention décrit également le dispositif de quantification de gain correspondant au procédé.
PCT/CN2009/070119 2008-01-31 2009-01-13 Procédé et dispositif de quantification d'un gain WO2009097763A1 (fr)

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Citations (5)

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US6104992A (en) * 1998-08-24 2000-08-15 Conexant Systems, Inc. Adaptive gain reduction to produce fixed codebook target signal
CN1468427A (zh) * 2000-05-19 2004-01-14 �����ɭ��ϵͳ��˾ 一种码激励线性预测语音编码器的增益量化
CN1151492C (zh) * 1995-05-03 2004-05-26 艾利森电话股份有限公司 综合-分析线性预测语音编码中的增益量化方法
CN1820306A (zh) * 2003-05-01 2006-08-16 诺基亚有限公司 可变比特率宽带语音编码中增益量化的方法和装置
CN101030378A (zh) * 2006-03-03 2007-09-05 北京工业大学 一种建立增益码书的方法

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FI113571B (fi) * 1998-03-09 2004-05-14 Nokia Corp Puheenkoodaus

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1151492C (zh) * 1995-05-03 2004-05-26 艾利森电话股份有限公司 综合-分析线性预测语音编码中的增益量化方法
US6104992A (en) * 1998-08-24 2000-08-15 Conexant Systems, Inc. Adaptive gain reduction to produce fixed codebook target signal
CN1468427A (zh) * 2000-05-19 2004-01-14 �����ɭ��ϵͳ��˾ 一种码激励线性预测语音编码器的增益量化
CN1820306A (zh) * 2003-05-01 2006-08-16 诺基亚有限公司 可变比特率宽带语音编码中增益量化的方法和装置
CN101030378A (zh) * 2006-03-03 2007-09-05 北京工业大学 一种建立增益码书的方法

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